Metrics Evaluation
Explore metrics evaluation in machine learning to understand how to measure model performance both offline and online. Learn to assess models using metrics like logloss, MAE, R2, and business impact metrics such as click-through rate and revenue lift. Gain insight into staging with real traffic and the role of A/B testing in validating production models.
We'll cover the following...
We'll cover the following...
Metrics evaluation
In practice, it’s common that the model performs well during offline evaluation but does not perform well when in production. Therefore, it is important to measure model performance in both on and offline environments.
Offline metrics
- During offline training and evaluating, we use metrics like logloss,
MAE Mean Absolute Error